Orion: A Unified Visual Agent for Multimodal Perception, Advanced Visual Reasoning and Execution
N Dinesh Reddy, Sudeep Pillai
2025-11-19
Summary
This paper introduces Orion, a new system for visual AI that can both understand what's in an image and then *do* things with that understanding, like answer complex questions or perform tasks based on the image.
What's the problem?
Existing vision-language models are good at *describing* what they see in an image, but they struggle with tasks that require multiple steps or using specialized tools to really analyze the image. They're kind of like being able to say 'there's a car' but not being able to figure out its make, model, or how fast it's going.
What's the solution?
Orion solves this by acting like an 'agent' that can call upon a variety of computer vision tools – things like object detectors, tools that find specific points in an image, and even tools that can read text within the image. It doesn't just *see* the image, it *uses* tools to break down the problem into smaller steps and then combine the results to get a final answer or complete a task. It's like giving the AI a toolbox and letting it figure out how to use the right tools for the job.
Why it matters?
Orion represents a shift towards more practical and intelligent visual AI. Instead of just understanding images passively, it can actively reason about them and perform complex tasks, bringing us closer to AI systems that can truly 'see' and interact with the world around them. This moves visual AI from research to real-world applications.
Abstract
We introduce Orion, a visual agent framework that can take in any modality and generate any modality. Using an agentic framework with multiple tool-calling capabilities, Orion is designed for visual AI tasks and achieves state-of-the-art results. Unlike traditional vision-language models that produce descriptive outputs, Orion orchestrates a suite of specialized computer vision tools, including object detection, keypoint localization, panoptic segmentation, Optical Character Recognition, and geometric analysis, to execute complex multi-step visual workflows. The system achieves competitive performance on MMMU, MMBench, DocVQA, and MMLongBench while extending monolithic vision-language models to production-grade visual intelligence. By combining neural perception with symbolic execution, Orion enables autonomous visual reasoning, marking a transition from passive visual understanding to active, tool-driven visual intelligence.